A future of automated image contouring with machine learning in radiation therapy

Abstract

Automated image contouring is showing improvements in efficiency for a number of clinical tasks in radiotherapy. While atlas segmentation has proven moderately beneficial, the next generation of algorithms based on convolutional neural networks is already pointing to improvements in precision and efficiency. This work provides a broad overview of the benefits of machine learning when applied to these tasks.